Portfolio Performance Manipulation and Manipulation-Proof Performance Measures

By W. Goetzmann, Jonathan E. Ingersoll, Matthew I. Spiegel, Ivo Welch. 2007

600 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/51bb77035cac7e07e5119b0fd769af08b99dacce

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Finance

Citations in the corpus

Out-of-Sample Predictions of Bond Excess Returns and Forward Rates: An Asset Allocation Perspective (2010, positive): “In order to take into account these concerns, we follow Goetzmann et al. (2007), who suggest a set of conditions under which a manipulation-proof measure exists.”
A Lottery Demand-Based Explanation of the Beta Anomaly (2017, positive): “…of that generated by the unconditional portfolio analysis (Table 12In Section IV and Table A3 of the online appendix, we demonstrate that the cross-sectional patterns in MAX decile portfolio performance are robust when using the manipulation proof performance measure of Ingersoll et al. (2007).”
On the sources of uncertainty in exchange rate predictability (2018, positive): “In order to take account of concerns about datamining in light of our search over multiple predictors, we employ critical values computed using a data-mining robust bootstrap technique proposed in Inoue and Kilian (2005), which we adjust to allow for cross-country correlation.”
Understanding Index Option Returns (2009, background): “The results are similar using alternative measures, such as Leland’s alpha (Leland 1999) or the manipulation proof performance measure ( Goetzmann et al. 2007 ).”
Portfolio performance evaluation with loss aversion (2010, neutral): “( 2007 ) presented yet another approach to the construction of utility-based performance measures.”
Calibrated Incentive Contracts (2013, neutral): “Lo (2001), Goetzmann et al. (2007) and Foster and Young (2010) all emphasize the fragility of many performance measures to gaming by the agent, as well as the difficulty of both rewarding and screening agents.”
A Unique View of Hedge Fund Derivatives Usage: Safeguard or Speculation? (2012, result): “Buying stocks in which 20Alternatively, this finding is also consistent with a greater manipulation of the Sharpe Ratio among hedge fund advisors that report long positions in individual equity options (see, e.g., Goetzmann et al. (2007)).”
The Price of Correlation Risk: Evidence from Equity Options (2009, background): “It is therefore important to analyze the excess returns in more detail, as Sharpe ratios may not fully reveal the risk of a strategy based on derivatives (Ingersoll et al. (2007)). We do this in several different ways. First, we estimate the CAPM beta and alpha of the strategy. The CAPM beta is 0.02”
Volatility‐Managed Portfolios (2017, methodology): “In the Internet Appendix, we show that our strategy works for a credit-risk factor formed from excess corporate bond returns; that it works for international stock market indices; that it can be further improved through the use of more sophisticated models of variance forecasting; that it does not g”